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Gender-Specific Pathways in Violent Crime: Investigating the Role of Demographic and Mental Health Factors Using Mixed Graphical Models and Bayesian Networks
Journal of Interpersonal Violence ( IF 2.621 ) Pub Date : 2024-03-04 , DOI: 10.1177/08862605241234658
Wen-Jing Yan 1, 2 , Jun-Hao Zhao 1, 3 , Li Chen 1, 2
Affiliation  

This research aims to uncover gender-specific relationships and pathways that contribute to the perpetration of violent crimes, using sophisticated analytical tools to analyze the complex interactions between various factors. Employing Mixed Graphical Models and Bayesian networks, the study analyzes a sample of 1,254 prisoners (61.64% males and 38.36% females) to investigate the relationships among demographic factors, mental health issues, and violent crime. The study utilizes comprehensive measures, including the Beck Depression Inventory, Beck Anxiety Inventory, and Childhood Trauma Questionnaire, to assess participants’ mental health status.Key findings reveal significant gender differences in the pathways to violent crime. For males, incomplete parental marriages strongly correlate with criminal behavior severity, while marriage status emerges as a significant factor, with married males less likely to commit violent crimes. In contrast, these relationships are not significant for females. Bayesian network analysis indicates that living in urban areas differently influences education and emotional expression across genders, emphasizing the importance of contextual factors. The study highlights the need for gender-specific considerations in criminal justice policies and interventions. It underscores the complex interplay of demographic and mental health factors in influencing violent crime pathways, providing insights for developing more effective prevention strategies. Despite its cross-sectional design and reliance on self-reported data, the research significantly contributes to understanding the gendered dimensions of criminal behavior.

中文翻译:

暴力犯罪中的特定性别途径:使用混合图形模型和贝叶斯网络调查人口和心理健康因素的作用

这项研究旨在利用复杂的分析工具来分析各种因素之间复杂的相互作用,从而揭示导致暴力犯罪的特定性别关系和途径。该研究采用混合图形模型和贝叶斯网络,分析了 1,254 名囚犯(61.64% 男性和 38.36% 女性)的样本,以调查人口因素、心理健康问题和暴力犯罪之间的关系。该研究利用贝克抑郁量表、贝克焦虑量表和童年创伤问卷等综合措施来评估参与者的心理健康状况。主要发现揭示了暴力犯罪途径中的显着性别差异。对于男性来说,不完整的父母婚姻与犯罪行为的严重程度密切相关,而婚姻状况则是一个重要因素,已婚男性实施暴力犯罪的可能性较小。相比之下,这些关系对于女性来说并不重要。贝叶斯网络分析表明,生活在城市地区对不同性别的教育和情感表达有不同的影响,强调了背景因素的重要性。该研究强调了在刑事司法政策和干预措施中考虑具体性别的必要性。它强调了人口和心理健康因素在影响暴力犯罪途径方面的复杂相互作用,为制定更有效的预防策略提供了见解。尽管该研究采用横断面设计并依赖于自我报告的数据,但它对理解犯罪行为的性别维度做出了重大贡献。
更新日期:2024-03-04
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